Abstract: A process and system for the analysis and/or control of a mixture of liquid hydrocarbons and biodiesel to determine biodiesel concentration includes a) measuring the near infrared absorption in at least two of the bands of two absorption bands from a portion of the range of 800-2500 nm; in particular 1100-2500 nm which are used to quantify the biodiesel content. b) taking each of the absorbances measured, or a mathematical function thereof, c) performing at least one mathematical computing or statistical treatment using the above absorbances or functions as individual independent variables, d) assigning and applying weighting constants or their equivalents to the independent variables, and, optionally e) applying the above steps using known compositions to calibrate the instrument and determine the weighting constants or equivalents, and further optionally f) outputting a signal indicative of the biodiesel concentration in the mixture, based on the absorbances or functions.

Abstract: A Fourier-Transform Raman spectrometer was used to collect the Raman spectra of (208) commercial petroleum fuels. The individual motor and research octane numbers (MON and RON, respectively) were determined experimentally using the industry standard ASTM knock engine method. Partial Least Squares (PLS) regression analysis can be used to build regression models which correlate the Raman spectra (175) of the fuels with the experimentally determined values for MON, RON, and pump octane number (the average of MON and RON) of the fuels. Each of the models was validated using leave-one-out validation. The standard errors of validation (SEV) are 0.415, 0.535, and 0.410 octane numbers for MON, RON, and pump octane number, respectively. By comparing the standard error of validation to the standard deviation for the experimentally determined octane numbers, it is evident that the accuracy of the Raman determined values is limited by the accuracy of the training set used in creating the models.